I trained both as a scientist and as a physician and, throughout my career, I have focused on the treatment and biology of ovarian cancer (OvCa). My Ph.D. thesis was on the role of proteases in ovarian cancer and my clinical fellowship involved a special emphasis on the treatment of patients with this disease. As a surgeon and clinician, I am familiar with the presentation of ovarian cancer in patients, and experience the incredible obstacles we face in its treatment. In the laboratory, I have built the research infrastructure necessary for effective ovarian cancer research.
The Lengyel lab has elucidated, at least in part, the first critical steps of ovarian cancer metastasis by paying close attention to the host microenvironment. We have collected the 25 most commonly used ovarian cancer cell lines from all over the world, including those which are chemotherapy resistant. We have established several mouse models for OvCa, and using a genetic mouse model (K-rasG12D/+/Pten-/- -- established by Dr. Tyler Jacks), a syngeneic orthotopic mouse model using mouse OvCa cells (ID8 -- established by K. Roby), and several xenograft ip models using primary and cultured human OvCa cells. I have also established a prospective OvCa tissue bank and, together with 2 gynecologic pathologists, we have assembled 13 tissue arrays including normal tissue, borderline tumor and primary tumor, & corresponding metastasis. As a surgeon, the main focus of my practice is patients with OvCa; therefore, I will be able to enroll a substantial number of patients on the proposed clinical trial and have the infrastructure in place to collect the tissue required for the translational studies.
My clinical experience treating ovarian cancer, together with my laboratory, which focuses on OvCa biology, gives me a unique opportunity and obligation to find new treatments that can benefit patients with ovarian cancer.
University of Munich
Munich
M.D. - M.D.
1992
AI-based automated segmentation for ovarian/adnexal masses and their internal components on ultrasound imaging.
AI-based automated segmentation for ovarian/adnexal masses and their internal components on ultrasound imaging. J Med Imaging (Bellingham). 2024 Jul; 11(4):044505.
PMID: 39114540
Molecular changes driving low-grade serous ovarian cancer and implications for treatment.
Molecular changes driving low-grade serous ovarian cancer and implications for treatment. Int J Gynecol Cancer. 2024 Jul 02.
PMID: 38950921
Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness.
Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness. Cell Death Dis. 2024 May 28; 15(5):370.
PMID: 38806454
5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer.
5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer. Gynecol Oncol. 2024 03; 182:82-90.
PMID: 38262243
Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression.
Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression. medRxiv. 2023 Nov 13.
PMID: 38014221
Adipocytes reprogram cancer cell metabolism by diverting glucose towards glycerol-3-phosphate thereby promoting metastasis.
Adipocytes reprogram cancer cell metabolism by diverting glucose towards glycerol-3-phosphate thereby promoting metastasis. Nat Metab. 2023 09; 5(9):1563-1577.
PMID: 37653041
Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort.
Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort. JAMA Netw Open. 2023 07 03; 6(7):e2323289.
PMID: 37440228
Normal saline remodels the omentum and stimulates its receptivity for transcoelomic metastasis.
Normal saline remodels the omentum and stimulates its receptivity for transcoelomic metastasis. JCI Insight. 2023 06 22; 8(12).
PMID: 37345662
Decoding evolutionary trajectories of ovarian cancer metastasis.
Decoding evolutionary trajectories of ovarian cancer metastasis. Cancer Cell. 2023 06 12; 41(6):1008-1010.
PMID: 37311411
Understanding Long-Term Survival of Patients with Ovarian Cancer-The Tumor Microenvironment Comes to the Forefront.
Understanding Long-Term Survival of Patients with Ovarian Cancer-The Tumor Microenvironment Comes to the Forefront. Cancer Res. 2023 05 02; 83(9):1383-1385.
PMID: 37128849